Package: BTM
Type: Package
Title: Biterm Topic Models for Short Text
Version: 0.3.8
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c(
    person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), 
    person('BNOSAC', role = 'cph', comment = "R wrapper"), 
    person('Xiaohui Yan', role = c('ctb', 'cph'), email = 'xhcloud@gmail.com', comment = "BTM C++ library"))
Description: Biterm Topic Models find topics in collections of short
        texts. It is a word co-occurrence based topic model that learns
        topics by modeling word-word co-occurrences patterns which are
        called biterms. This in contrast to traditional topic models
        like Latent Dirichlet Allocation and Probabilistic Latent
        Semantic Analysis which are word-document co-occurrence topic
        models. A biterm consists of two words co-occurring in the same
        short text window. This context window can for example be a
        twitter message, a short answer on a survey, a sentence of a
        text or a document identifier. The techniques are explained in
        detail in the paper 'A Biterm Topic Model For Short Text' by
        Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Xueqi Cheng (2013)
        <https://github.com/xiaohuiyan/xiaohuiyan.github.io/blob/master/paper/BTM-WWW13.pdf>.
License: Apache License 2.0
URL: https://github.com/bnosac/BTM
Encoding: UTF-8
Imports: Rcpp, utils
Suggests: udpipe, data.table
LinkingTo: Rcpp
RoxygenNote: 7.3.2
Repository: https://bnosac.r-universe.dev
Date/Publication: 2025-11-26 19:50:21 UTC
RemoteUrl: https://github.com/bnosac/btm
RemoteRef: HEAD
RemoteSha: ce50e78856d8ec1cba127a5232bd1ad0481930fc
NeedsCompilation: yes
Packaged: 2026-06-24 02:26:18 UTC; root
Author: Jan Wijffels [aut, cre, cph] (R wrapper),
  BNOSAC [cph] (R wrapper),
  Xiaohui Yan [ctb, cph] (BTM C++ library)